The Intersection of Artificial Intelligence in Human Resource Management: An Exploration of Talent Communication

dc.contributor.advisorValecha, Rohit
dc.contributor.advisorRao, H. Raghav
dc.contributor.authorVotto, Alexis Megan
dc.contributor.committeeMemberNajafirad "Rad", Peyman "Paul"
dc.contributor.committeeMemberKeeton, Katheryn
dc.descriptionThe author has granted permission for their work to be available to the general public.
dc.description.abstractWithin this research, we sought to explore and understand where Artificial Intelligence (AI) intersects with human resource information systems. We further investigated the AI phenomenon by leveraging machine learning tools to understand the following: 1) where AI exists within human resource management (HRM) via a systematic literature review ; 2) how to propose a research framework to investigate data science competencies within private and federal sector job postings, and 3) how military veterans with data science skills communicate their experience concerning employability. The following sections discuss these papers further. Paper 1: Artificial intelligence in tactical human resource management: A systematic literature review (2021) The first essay is a systematic literature review investigating where AI exists within published HRM literature. Within this literature review, we leveraged a 2-phased methodology to navigate 315,053 articles from various multidisciplinary publication sources. The findings of this review indicate research opportunities to grow within HRM's competency management systems (pay and benefits). Furthermore, it highlighted a gap within AI research exploring qualitative components of recruitment information systems, which spurred the motivation for the rest of this dissertation. Paper 2: JC-Compass: A Framework for Conducting Competency-Based Job Posting Research and Analysis (In Progress) The second essay proposes a research framework to conduct competency-based job description research. This paper leverages a design science approach to propose and explore a new competency-based job description research method. The results indicate that the federal sector potentially places a decisive influence on problem-solving terms rather than artificial intelligence terms. We also discovered that the private sector strongly influenced statistics and ethics terminology, whereas the federal focused on problem solving and ethics. Paper 3: Veteran Talent within Data Science: An Exploratory Resume Analysis on the Employability of Active-Duty Veterans The third and final paper explores how military veterans seeking jobs within the data science community communicate their skills and how their employability is affected by their choice of words within resumes. Understanding that drawdowns are posturing some military veterans to leave the service and pursue other endeavors, we sought to evaluate how Gulf War II ("post 9/11") veterans advertise their skills relative to how many times they have been unemployed throughout their resume. In conducting this research, we aspire to provide insight into how veterans seeking data science jobs could better posture themselves to be more marketable and provide employers insight into current trends and expectations.
dc.description.departmentInformation Systems and Cyber Security
dc.format.extent204 pages
dc.subjectArtificial Intelligence
dc.subjectHuman Resource Information Systems
dc.subjectHuman Resource Management
dc.subjectMachine Learning
dc.subjectNatural Language Processing
dc.subjectTalent Management
dc.subject.classificationArtificial intelligence
dc.subject.classificationLabor relations
dc.subject.classificationInformation science
dc.titleThe Intersection of Artificial Intelligence in Human Resource Management: An Exploration of Talent Communication
dcterms.accessRightspq_OA Systems and Cyber Security of Texas at San Antonio of Philosophy


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